Lead ML Engineer - MLOps & Cloud AI at Scale

Capital One; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking a Lead Machine Learning Engineer to productionize ML applications at scale. You will design and implement ML models, build data pipelines, and ensure high availability of ML systems in Agile teams.

Expertise in Python/Scala/Java, PyTorch or TensorFlow, and cloud platforms is required. The role emphasizes end-to-end ML engineering, from data pipelines to model governance, with opportunities for leadership and impact across Capital One's AI initiatives.

Qualifications

• Bachelor’s degree required in CS, EE, math, or a related field.
• 6+ years designing data-intensive, distributed computing solutions.
• 4+ years programming with Python, Scala, or Java.
• 2+ years building, scaling, and optimizing ML systems.

Responsibilities

• Design, build, and deliver ML models and components for real-world problems with product and DS teams.
• Inform infrastructure decisions using ML modeling techniques and data considerations.
• Write, test, and deploy application code; validate ML models.
• Collaborate in a cross-functional Agile team to enable state-of-the-art data and ML apps.
• Retrain, monitor, and maintain models in production.
• Leverage cloud architectures to deliver ML models at scale.
• Construct data pipelines to feed ML models.
• Follow CI/CD and monitoring practices to ensure reliable deployments.
• Ensure governance and responsible AI practices in code and models.
• Use Python, Scala, or Java for development.

Skills

Distributed computing

Python/Scala/Java programming

ML systems

Education

Bachelor’s degree in CS/EE/math

Master/PhD (preferred)

Tools

PyTorch

TensorFlow

scikit-learn

Spark

Dask

Job description

Capital One is seeking a Lead Machine Learning Engineer to productionize ML applications at scale. You will design and implement ML models, build data pipelines, and ensure high availability of ML systems in Agile teams.

Expertise in Python/Scala/Java, PyTorch or TensorFlow, and cloud platforms is required. The role emphasizes end-to-end ML engineering, from data pipelines to model governance, with opportunities for leadership and impact across Capital One's AI initiatives.